Drivers of C cycling in three arctic-alpine plant communities

Figures & data

Figure 1. Hypothesized framework for growing-season C fluxes: gross ecosystem photosynthesis depends on total aboveground biomass (Biomass_above), community-weighted mean of specific leaf area (SLA_CWM), and soil moisture (Hypothesis 1). Aboveground respiration (R_above) depends on Biomass_above and SLA_CWM (Hypothesis 2a). Belowground respiration (R_below) depends on root biomass (Biomass_roots), microbial activity, and SLA_CWM, where SLA_CWM in this context represents leaf decomposability (Hypothesis 2b). Microbial activity depends on vegetation woodiness, represented by the C:N ratio of aboveground vegetation (C:Nratio above), and on nutrient availability and leaf recalcitrance as represented by SLA_CWM (Hypothesis 3). Dashed lines between variables indicate important relationships not tested in this study. The framework is based on Wookey et al. (2009); Clemmensen et al. (2015); Veen, Sundqvist, and Wardle (2015); Parker, Subke, and Wookey (2015); and Becklin, Pallo, and Galen (2012).

Table 1. Community means ± SD for alpine Empetrum-dominated heath, meadow, and Salix-shrub plant communities in Dovre Mountains, central Norway.

Community	Heath	SD	Meadow	SD	Shrub	SD
Three most dominant species	Arctostaphylus uva-ursi (L.) Spreng.		Avenella flexousa (L.) Drejer		Avenella flexousa (L.) Drejer
	Empetrum nigrum hermaphroditum L.		Festuca ovina L.		Salix lapponum L.
	Festuca ovina L.		Anthoxanthum nipponicum Honda		Salix glauca L.
Snow depth maximum (cm)	2.41 ± 2.10		39.56 ± 4.76		58.50 ± 18.59
Soil moisture June (%)	18.65 ± 2.41		28.45 ± 3.29		60.11 ± 31.19
Soil moisture July (%)	22.51 ± 2.27		53.06 ± 14.97		46.23 ± 25.86
Soil moisture September (%)	28.95 ± 3.44		39.25 ± 5.78		37.33 ± 7.81
Tair (°C)	22.80 ± 3.77		23.08 ± 2.79		22.26 ± 2.42
Tsurface (°C)	15.65 ± 5.13		13.65 ± 2.82		12.20 ± 2.60
Tsoil (°C)	10.23 ± 1.35		8.90 ± 1.53		8.95 ± 0.80
Tsurface summer mean	10.30 ± 0.74		10.09 ± 0.54		9.08 ± 1.12
Tsurface summer minimum	2.50 ± 0.80		2.00 ± 0.76		2.00 ± 0.93
Tsurface summer maximum	15.00 ± 6.22		18.00 ± 3.87		13.00 ± 5.64
Tsurface winter mean	−3.03 ± 0.49		−1.05 ± 0.23		−0.76 ± 0.42
Tsurface winter minimum	−6.75 ± 0.55		−3.25 ± 0.61		−2.75 ± 0.71
Tsurface winter maximum	−0.50 ± 0.33		−0.50 ± 0.23		−0.50 ± 0.16
Growing degree hours	9040 ± 1709		8403 ± 1056		6663 ± 1801
pH minimum	3.53 ± 0.40		4.38 ± 0.27		3.51 ± 0.27
Soil organic carbon (kg C m^–2)	7.387 ± 2.59		10.713 ± 2.88		4.90 ± 2.26
Soil total nitrogen (kg N m^–2)	0.38 ± 0.15		0.80 ± 0.23		0.43 ± 0.18
SLACWM (mm^2 mg^–1)	6.78 ± 0.69		16.28 ± 2.37		11.50 ± 1.90
LDMCCWM (mg g^–1)	462.19 ± 14.04		345.62 ± 23.17		378.65 ± 33.06
LACWM (mm^2)	37.67 ± 7.25		196.23 ± 67.62		268.18 ± 131.88
Hyphal ingrowth (mg g^–1)	0.022 ± 0.031		-		0.028 ± 0.053

Note. The three most dominant species within each community are based on total number of hits in each community, recorded on each plot with the point intercept method 25 × 25 cm quadrat and twenty-five pins (n = 96). Snow depth is maximum depth across March 2015 and April 2016 (n = 17). Soil moisture was measured on June 10 in the shrub and June 11 in the meadow and heath communities, and it was also measured on July 21 in the heath, July 22 in the shrub, and July 23 in the meadow. Soil moisture was measured on September 28 in all three communities (n = 17). Temperature inside the CO₂ chamber (T_air), surface temperature (T_surface), and soil temperature (T_soil) was obtained during CO₂ measurements. Summer T_surface is surface temperature across the warmest months, July and August 2015, and winter T_surface is across the coldest months, January and February 2015 (n = 24). Growing degree hours are the sum of hours where surface temperature was greater than 5°C (sensu Graae et al. 2012; n = 24). Minimum pH, soil organic carbon, and soil total nitrogen was from throughout the full soil pit with a mean depth of 56 ± 8 cm (n = 17). Amount of aboveground vegetation of total vegetation biomass is reflected in proportion of vegetation carbon above- and belowground (n = 17). Community-weighted means of specific leaf area (SLA_CWM), leaf dry matter content (LDMC_CWM), and leaf area (LA_CWM; n = 17). Hyphal ingrowth (mg g^–1) was for 5 × 3.5 cm sand bags made of 50 µm nylon with placed in each community (n = 24).

Table 2. Effects (µmol m^–2 s^–1) SD^–1of each variable in full models across community. Explanatory variables were z-standardized (x – mean(x))/sd(x) so one unit change corresponds to one SD. Models were run without log transformation to ease understanding of the effects. Sum of squares ($\chi$²) and p values were derived from a likelihood-ratio test (Chi-square test) performed on backward model selection (drop1 function in R; n = 17). Significant effects are bold.

Response	Explanatory Variables	Effect (µmol m^–2 s^–1) SD^–1	SE	$\chi$^2(1)	p Value
GEP600	Intercept	9.51	± 0.58
	zSLACWM	0.60	± 0.60	3.72	0.256
	zMoisture	2.93	± 1.05	28.16	0.005
	zBiomassabove	−0.74	± 0.59	5.66	0.165
Rabove	Intercept	1.29	± 0.20
	zSLACWM	−0.09	± 0.21	0.12	0.644
	zBiomassabove	0.34	± 0.22	1.69	0.108
Rbelow	Intercept	3.86	± 0.32
	zSLACWM	1.19	± 0.36	18.85	0.001
	zBiomassroots	0.17	± 0.40	0.31	0.626
	zMicrobessum	0.04	± 0.45	0.01	0.923

Table 3. Gross ecosystem photosynthesis model selection based on AICc on multiple linear models, testing Hypothesis 1. GEP was standardized to 600 PAR (GEP₆₀₀) and log-transformed. Soil moisture (%), specific leaf area (SLA_CWM; mm^–2 mg^–1), and aboveground biomass (Biomass_above; g DW m^–2) were z-standardized. Akaike weight values (w) is the probability a model is best, given the set of models considered. R² adjusted was calculated for each model (n = 17).

Model Rank	Model Parameters	Intercept	zSLACWM	zBiomassabove	zMoisture	df	logLik	AICc	ΔAICc	w	R^2 Adjusted
m1	ln(GEP600) ~ 1 + zBiomassabove + zMoisture	2.24	NA	−0.12	0.42	4	3.19	4.95	0	0.68	0.52
m2	ln(GEP600) ~ 1 + zSLACWM + zBiomassabove + zMoisture	2.21	0.09	−0.07	0.32	5	4.36	6.73	1.79	0.28	0.55
m3	ln(GEP600) ~ 1 + zSLACWM + zBiomassabove	2.1	0.2	0.03	NA	4	0.46	10.41	5.47	0.04	0.33
m4	ln(GEP600) ~ 1 + zBiomassabove	2.09	NA	−0.05	NA	3	−3.92	15.69	10.74	0	−0.04
m5	ln(GEP600) ~ 1 + zMoisture	2.12	NA	NA	0.14	3	−8.25	23.83	18.88	0	0.09
m6	ln(GEP600) ~ 1 + zSLACWM + zMoisture	2.11	0.07	NA	0.12	4	−7.83	26	21.06	0	0.08
m7	ln(GEP600) ~ 1 + zSLACWM	2.06	0.16	NA	NA	3	−10.88	28.95	24.01	0	0.1
m8	ln(GEP600) ~ 1	2.06	NA	NA	NA	2	−12.67	29.92	24.97	0	0

Figure 2. Full model variable relationships when plotting one variable and keeping the others constant. Relationships are across community and within community, based on growing-season measurements in alpine Empetrum-heath, meadow, and Salix-shrub plant communities in Dovre Mountains, central Norway (n = 17). Lines drawn are for significant variables across (red) and within community (black dashed line), tested with a likelihood-ratio test (Chi-square test) performed on backward model selection (drop1 function in R). Top (A–C): Gross ecosystem photosynthesis standardized to 600 PAR (GEP₆₀₀; µmol m⁻² s⁻¹) and the variables community-weighted means of specific leaf area (SLA_CWM; mm⁻² mg⁻¹), total aboveground biomass (Biomas_above; g DW m^–2), and soil moisture (%). Middle (D,E): Estimated aboveground respiration standardized to 20°C (R_above; µmol m^–2 s^–1) and the variables SLA_CWM and Biomass_above (g DW m^–2). Bottom (F–H): Estimated belowground respiration standardized to 10°C (R_below) and the variables SLA_CWM, root biomass (Biomass_roots; g DW m^–2), sum of all measured microbial activity (Microbes_sum; nmol h^–1 m^–2). Biomass _roots and Microbes_sum was summed across the total soil pit with mean depth 56 ± 8 cm.

Table 4. Aboveground respiration (R_above) model selection based on AICc on multiple linear models, testing Hypothesis 2a. R_above was standardized to 20°C and log-transformed. Specific leaf area (SLA_CWM; mm^–2 mg^–1) and aboveground biomass (Biomass_above; g DW m^–2) were z-standardized. Akaike weight values (w) is the probability a model is best, given the set of models considered. R² adjusted were calculated for each model (n = 17).

Model Rank	Model Parameters	Intercept	zSLACWM	zBiomassabove	df	logLik	AICc	ΔAICc	w	R^2 Adjusted
m1	ln(Rabove) ~ 1 + zBiomassabove	0.05	NA	0.41	3	−13.08	34.01	0	0.55	0.32
m2	ln(Rabove) ~ 1 + zSLACWM + zBiomassabove	0.04	−0.19	0.33	4	−11.96	35.25	1.24	0.29	0.36
m3	ln(Rabove) ~ 1 + zSLACWM	0.04	−0.31	NA	3	−14.68	37.21	3.21	0.11	0.18
m4	ln(Rabove) ~ 1	0.05	NA	NA	2	−16.92	38.69	4.68	0.05	0

Table 5. Belowground respiration (R_below) model selection based on AICc on multiple linear models, testing Hypothesis 2b. R_below was standardized to 10°C and log-transformed. Specific leaf area (SLA_CWM; mm^–2 mg^–1), the sum of microbial activity (Microbes_sum; nmol h^–1 m^–2), and standing root biomass (Biomass_roots; g DW m^–2) were z-standardized. Akaike weight values (w) is the probability a model is best, given the set of models considered. R² adjusted were calculated for each model (n = 17).

Model Rank	Model Parameters	Intercept	zSLACWM	zBiomassroots	zMicrobessum	df	logLik	AICc	ΔAICc	w	R^2 Adjusted
m1	ln(Rbelow) ~ 1 + zSLACWM	1.24	0.28	NA	NA	3	−4.19	15.57	0	0.44	0.45
m2	ln(Rbelow) ~ 1 + zSLACWM + zMicrobessum	1.26	0.28	NA	0.07	4	−2.61	16.55	0.98	0.27	0.51
m3	ln(Rbelow)~ 1 + zSLACWM + zBiomassroots	1.26	0.3	0.05	NA	4	−2.77	16.88	1.3	0.23	0.5
m4	ln(Rbelow)~ 1 + zSLACWM + zMicrobessum + zBiomassroots	1.26	0.28	0.02	0.06	5	−2.59	20.63	5.05	0.04	0.48
m5	ln(Rbelow)~ 1 + zMicrobessum	1.25	NA	NA	0.22	3	−7.44	22.72	7.15	0.01	0.2
m6	ln(Rbelow)~ 1 + zMicrobessum + zBiomassroots	1.25	NA	0	0.22	4	−7.44	26.21	10.64	0	0.14
m7	ln(Rbelow)~ 1 + zBiomassroots	1.25	NA	0.12	NA	3	−9.19	26.23	10.66	0	0.01
m8	ln(Rbelow)~ 1	1.24	NA	NA	NA	2	−11.99	28.55	12.98	0	0

Table 6. F value, degrees of freedom(df), and p value from one-way ANOVA tests of differences among enzyme activities (nmol h^–1 m^–2) between communities. The enzymes were from organic and mineral horizons, and total across the soil pit. The significant differences are bold. In the organic horizon b-gluc, cbh, xylo, and nag were significantly higher in the meadow than in the heath and shrub communities (p < 0.001, TukeyHSD). Activity of a-gluc in the meadow was only higher than the shrub community (p < 0.05, TukeyHSD).

Horizon	Enzyme	F Value	dfnum	dfden	p Value
Organic	ln(a-gluc)	12.36	2	13	0.00
	ln(b-gluc)	5.19	2	13	0.02
	ln(cbh)	18.97	2	13	0.00
	ln(xylo)	15.03	2	13	0.00
	ln(nag)	23.58	2	13	0.00
Mineral	ln(a-gluc)	0.31	2	15	0.74
	ln(b-gluc)	2.63	2	15	0.11
	cbh	0.52	2	15	0.60
	xylo	0.20	2	15	0.82
	nag	0.92	2	15	0.42
Total	ln(a-gluc)	0.73	2	15	0.50
	ln(b-gluc)	2.76	2	15	0.10
	ln(cbh)	7.56	2	15	0.01
	xylo	6.28	2	15	0.01
	nag	4.90	2	15	0.02

Figure 3. Mean enzyme activity ±SD of α-glucosidase (a-gluc), β-glucosidase (b-gluc), cellobiohydrolase (cbh), β-xylosidase (xylo), and N-acetylglucosaminidase (nag), (A) in nmol h^–1 m^–2 and (B) in µmol h^–1 gC^–1 m^–2 for alpine Empetrum-dominated heath, meadow, and Salix-shrub plant communities in Dovre Mountains, central Norway. Activity for each enzyme is the sum across the total soil pit with mean depth 56 ± 8 cm (n = 17). See activities in organic and mineral horizons in Figure S2, and statistical differences in Table 6 and Table S2.

Figure 4. Total enzyme activity of β-glucosidase (b-gluc), cellobiohydrolase (cbh), β-xylosidase (xylo) (C enzyme activity_sum) (nmol h^–1 m^–2) correlated with “vegetation woodiness” across alpine Empetrum-dominated heath, meadow, and Salix-shrub plant communities in Dovre Mountains, central Norway. Left, community-weighted mean of SLA (SLA_CWM; p = 0.009) and right, C:N ratio of aboveground vegetation (C:N ratio_Above-ground; n = 17).

Figure 5. Summary of results with respect to hypothesized mechanisms based on actual measurements of growing-season summer C fluxes GEP₆₀₀) and ecosystem respiration partitioned into estimated aboveground (R_above) and belowground respiration (R_below) in alpine Empetrum-heath, meadow, and Salix-shrub plant communities in Dovre Mountains, central Norway (n = 17). Up and down arrows indicate high or low values. Arrow style indicates a significant variable in the full model across community (red line), significant variable in simple correlation (red dashed line), significant variable within the community (black line), presumed relationship not tested in this study (black dashed line), nonsignificant variable across community (grey). The flux arrow width is proportional to its measured flux size transformed to gC m^–2 h^–1.

Figure 6. Summary of results with respect to suggested implications of shrub expansion based on actual measurements of growing-season summer C fluxes (GEP₆₀₀ and ecosystem respiration partitioned into estimated aboveground (R_above) and belowground respiration (R_below) in alpine Empetrum-heath, meadow, and Salix-shrub plant communities in Dovre Mountains, central Norway (n = 17). Up and down arrows indicate an increase or decrease in variables because of shrub expansion in the respective community. Arrow style indicates a significant variable within the community (black line), presumed relationship not tested in this study (black dashed line), nonsignificant variable across community (grey). The flux arrow width is proportional to its measured flux size transformed to gC m^–2 h^–1. The transparent arrows correspond to the flux in the community invaded by shrubs.

Wookey, P. A., R. Aerts, R. D. Bardgett, F. Baptist, K. A. Bråthen, J. H. C. Cornelissen, L. Gough, I. P. Hartley, D. W. Hopkins, S. Lavorels, et al. 2009. Ecosystem feedbacks and cascade processes: Understanding their role in the responses of Arctic and alpine ecosystems to environmental change. Global Change Biology 15:1153–72. doi:10.1111/j.1365-2486.2008.01801.x.

 Web of Science ®Google Scholar

Clemmensen, K. E., R. D. Finlay, A. Dahlberg, J. Stenlid, D. A. Wardle, and B. D. Lindahl. 2015. Carbon sequestration is related to mycorrhizal fungal community shifts during long-term succession in boreal forests. New Phytologist 205 (4):1525–36. doi:10.1111/nph.13208.

 PubMed Web of Science ®Google Scholar

Veen, C. G. F., M. K. Sundqvist, and D. A. Wardle. 2015. Environmental factors and traits that drive plant litter decomposition do not determine home-field advantage effects. Functional Ecology 29 (7):1365–2435. doi:10.1111/1365-2435.12421.

 Web of Science ®Google Scholar

Parker, T. C., J. A. Subke, and P. A. Wookey. 2015. Rapid carbon turnover beneath shrub and tree vegetation is associated with low soil carbon stocks at a subarctic treeline. Global Change Biology 21 (5):2070–81. doi:10.1111/gcb.12793.

 Web of Science ®Google Scholar

Becklin, K. M., M. L. Pallo, and C. Galen. 2012. Willows indirectly reduce arbuscular mycorrhizal fungal colonization in understorey communities. Journal of Ecology 100 (2):343–51. doi:10.1111/j.1365-2745.2011.01903.x.

 Web of Science ®Google Scholar

Graae, B. J., P. De Frenne, A. Kolb, J. Brunet, O. Chabrerie, K. Verheyen, N. Pepin, T. Heinken, A. Zobel, A. Shevtsova, I. Nijs, and A. Milbau. 2012. On the use of weather data in ecological studies along altitudinal and latitudinal gradients. Oikos 121:3–19.

 Web of Science ®Google Scholar